Process Simulation Framework Design and Validation with Grinding Systems
Dr. S. Sridevi*, Associate Professor, Department of Computer Science India.
Manuscript received on September 22, 2019. | Revised Manuscript received on October 20, 2019. | Manuscript published on October 30, 2019. | PP: 2861-2869 | Volume-9 Issue-1, October 2019 | Retrieval Number: A1101109119/2019©BEIESP | DOI: 10.35940/ijeat.A1101.109119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Process Industrial & their complex control operations require comprehensive simulation software systems for modeling plant dynamics and analyzing gaps and to achieve optimal control efficiency. These models support in training plant engineers on various process scenarios in controlled pseudo real time environment. Higher degree of model designing customization, flexibility, scalability, cost efficiency and domain agnostic solution features, are the desired characteristics of any process simulation framework. This paper formulates prototype design of an integrated generic process simulator platform and its components, enabling intuitive and interactive representation of intelligent model formats, facts, knowledge, rules & behaviors. The benefits range from safer process training, analysis / synthesis of controller models; control optimization and theoretical learning. The simulation performance of proposed framework is verified through material fineness control modeling of rotary vertical grinding mill. The adaptive leaning features, with hybrid prediction model validations results in the simulation accuracy and results are compared with prevalent systems.
Keywords: Process Modeling, Simulators, Rule Engine, Knowledge base, Process Training.